Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
Hum Brain Mapp. 2013 Feb;34(2):487-500. doi: 10.1002/hbm.21455. Epub 2011 Nov 11.
Previous studies have shown that healthy anatomical as well as functional brain networks have small-world properties and become less optimal with brain disease. During sleep, the functional brain network becomes more small-world-like. Here we test the hypothesis that the functional brain network during wakefulness becomes less optimal after sleep deprivation (SD). Electroencephalography (EEG) was recorded five times a day after a night of SD and after a night of normal sleep in eight young healthy subjects, both during eyes-closed and eyes-open resting state. Overall synchronization was determined with the synchronization likelihood (SL) and the phase lag index (PLI). From these coupling strength matrices the normalized clustering coefficient C (a measurement of local clustering) and path length L (a measurement of global integration) were computed. Both measures were normalized by dividing them by their corresponding C-s and L-s values of random control networks. SD reduced alpha band C/C-s and L/L-s and theta band C/C-s during eyes-closed resting state. In contrast, SD increased gamma-band C/C-s and L/L-s during eyes-open resting state. Functional relevance of these changes in network properties was suggested by their association with sleep deprivation-induced performance deficits on a sustained attention simple reaction time task. The findings indicate that SD results in a more random network of alpha-coupling and a more ordered network of gamma-coupling. The present study shows that SD induces frequency-specific changes in the functional network topology of the brain, supporting the idea that sleep plays a role in the maintenance of an optimal functional network.
先前的研究表明,健康的解剖学和功能大脑网络具有小世界特性,并且随着大脑疾病的发展变得不那么理想。在睡眠期间,功能大脑网络变得更加具有小世界特性。在这里,我们测试了一个假设,即在睡眠剥夺(SD)后,清醒时的功能大脑网络会变得不那么理想。在 8 名年轻健康受试者中,在一夜 SD 和一夜正常睡眠后,每天五次记录脑电图(EEG),同时处于闭眼和睁眼静息状态。使用同步可能性(SL)和相位滞后指数(PLI)确定整体同步性。从这些耦合强度矩阵中,计算出归一化聚类系数 C(局部聚类的度量)和路径长度 L(全局集成的度量)。这两个度量值除以它们对应的随机控制网络的 C-s 和 L-s 值进行归一化。SD 降低了闭眼静息状态下的 alpha 波段 C/C-s 和 L/L-s 以及 theta 波段 C/C-s。相比之下,SD 在睁眼静息状态下增加了 gamma 波段 C/C-s 和 L/L-s。这些网络属性变化与睡眠剥夺引起的持续注意力简单反应时间任务中的表现缺陷相关,表明它们具有功能相关性。研究结果表明,SD 导致 alpha 耦合的网络更随机,gamma 耦合的网络更有序。本研究表明,SD 会引起大脑功能网络拓扑的特定频率变化,支持睡眠在维持最佳功能网络方面发挥作用的观点。